The present invention relates to a method in digital signal transmission over a channel for estimating in a receiver transmitted symbols from a transmitted radio signal, wherein the symbol estimation is effected in a channel equalizer in accordance with a selected viterbi algorithm, and wherein the method comprises the following method steps:
receiving and demodulating the transmitted signal to a received signal; PA1 sampling the received signal at at least one sampling time point per symbol; PA1 determining at least an initial value of the estimated channel impulse response, the channel estimate, with the aid of the sampled signal values; PA1 determining a symbol sampling time point; PA1 selecting filter coefficients of a prefilter and filtering the sampled signal values in the prefilter to obtain prefiltered, observed signal values; and PA1 generating at least preliminarily estimated symbols in accordance with the viterbi algorithm, with the aid of the prefiltered, observed signal values. PA1 The viterbi algorithm itself operates at a higher rate than the symbol rate. PA1 An adaptive, fractionally spaced prefilter is used prior to the viterbi analyzer. PA1 The channel is estimated and tracked explicitly and the coefficients in the prefilter and the metric calculation filter are calculated with the aid of the channel estimate obtained. PA1 The weighting factors are used when generating the prefilter and the metric calculation filter to enable a short channel estimate to be used, with litle loss in performance. PA1 Prediction times of different lengths are permitted for the coefficients in the prefilter.
The invention also relates to an arrangement for carrying out the method.
One problem which often occurs in the digital radio transmission of a signal over a channel is that a transmitted signal is subjected to noise and co-channel disturbance and also to multipath propagation which results in time dispersion. For instance, in the case of mobile telephony, the transmission properties of the radio channel shift as a result of the transmitter and receiver changing their mutual relative positions. These problems have been solved in time-shared digital radio transmission systems in that the signal sequences that are transmitted in a time slot have one or more synchronizing sequences and one or more data sequences. The synchronizing sequence is known to the receiver and the receiver is able to estimate the transmission properties of the channel, i.e. to make a channel estimate, with the aid of this sequence. The receiver estimates the symbols of the data sequence containing the information that is to be transmitted, with the aid of this channel estimate.
In certain cases, it is not sufficient to make a channel estimate only once with each time slot. In the case of long time slots, the transmitter and the receiver have time to change their mutual relative positions considerably within the duration of the time slot. This means that the transmission properties of the channel can also change considerably within the duration of the time slot, so that the estimation of the transmitted symbols made by the receiver will be deficient and the transmitted information therefore unclear or ambiguous. A radio receiver in which such disturbances are partially avoided is described in an article in IEEE Transactions on Information Theory, January 1973, pages 120-124, F. R. Magee, Jr. and J. G. Proakis: "Adaptive Maximum-Likelihood Sequence Estimation for Digital Signaling in the presence of Intersymbol Interference". The article describes a channel equalizer which includes a viterbi analyzer having an adaptive filter as a channel estimating circuit. Received symbols are compared successively with hypothetical symbols and those hypothetical symbols which coincide closest with the received symbols are selected successively to form an estimated symbol sequence. The parameters of the adaptive filter are adjusted successively to the changed channel, with the aid of the selected, decided symbols.
A description of the viterbi algorithm is given in an article by G. David Forney, Jr.: "The Viterbi Algorithm" in Proceedings of the IEEE, Vol. 61, No. 3, March 1973. The article also describes in some detail the state and state transitions of the viterbi algorithm and also how these state transitions are chosen so as to obtain the most probable sequence of symbols.
The signal transmission between transmitter and receiver may be connected with certain problems, despite performing sequence estimation and adaptive channel estimation in the aforedescribed manner. One reason for these deficiencies is that the signal bandwidth of the system exceeds the system symbol rate, so-called excess bandwidth, as is the case, for instance, in the North American mobile telephone system TIA IS-54. Another reason for these deficiencies is that the transmission properties of the channel can change quickly, for instance as a result of fading. Two different types of solution to the problem of symbol rate are known to the art, in which a MLSE-detector (Maximum-Likelihood Sequence Estimator) is used:
The first type of solution is described in an article by Yongbing Wan, et al, of NovAtel Communications Ltd.: "A Fractionally-Spaced Maximum-Likelihood Sequence Estimation Receiver in a Multipath Fading Environment" published in the Proceedings of IEEE, ICASSP 1992. According to this article, a received radio signal is sampled twice with each symbol and the channel estimation is effected with the aid of an adaptive filter that uses this double sampling rate. The symbol estimate is performed in a viterbi analyzer which also uses the double sampling rate. The delta metric values, i.e. deviations between the received and the hypothetical sequences, are calculated for both the sampling occasions per symbol and the two delta metric values are added to determine a best state transition according to the viterbi algorithm. When adapting the filter with the aid of the estimated symbols, a fictive symbol is inserted at each alternate sampling time point. These fictive symbols are produced by interpolation between the estimated symbols in a second filter. The proposed solution has certain drawbacks. It is necessary to sample the received symbols at highly specific time points, and the adaptive channel estimation is complex. The interpolation in the second filter results in delays which may impair the symbol estimation. Filters that are used in signal processing, for instance a transmitter filter or a receiver filter must be known filters. Receiver filters, which may contain coils and capacitors, cause particular problems due to aging, manufacturing accuracies and temperature variations.
Another solution of the first kind is given in a paper written by R. A. Iltis: "A Bayesian Maximum-Likelihood Sequence Estimation Algorithm for A-Priori Unknown Channel and Symbol Timing" Department of Electrical and Computer Engineering, University of California, Santa Barbara, Aug. 21, 1990. This paper also states that a received signal shall be sampled twice with each symbol. Symbol estimation is effected in accordance with a viterbi algorithm, which calculates two delta metric values for each symbol, and these two values are weighted in the metric calculation. The channel estimation is performed in an adaptive filter having filter coefficients of the spacing of a symbol time, although the coefficients are adapted with each sampling occasion, thus twice with each symbol. The solution given includes a comprehensive metric calculation and because the channel estimate used has its filter taps at a full symbol time spacing, it fails to solve the problem of symbol synchronization in respect of complicated rapidly varying excess bandwidth channels. Also, similar to the solution proposed by Yongbing Wan according to the aforegoing, a receiver filter must be known with high degree of accuracy in the receiver.
The aforesaid methods relating to the first type of problem solution for solving the problem of low symbol rate are relatively demanding with regard to the calculations that must be carried out. A method which relates to the second type of solution has been proposed in an article in IEEE Transactions on Communications, Vol. Com-22, No. 5, May 1974, written by G. Ungerboeck: "Adaptive Maximum-Likelihood Receiver for Carrier-Modulated Data-Transmission Systems". According to this article, a received radio signal is sampled several times with each symbol time and the sample signal is allowed to pass through a prefilter. The prefiltered signal is sampled down to symbol rate and is then processed in a viterbi analyzer, which produces estimated symbols. The sampled impulse response of the radio channel is estimated with the aid of a channel estimate, this response including both the actual channel between transmitter and receiver, transmitter filter and receiver filter and also the prefilter. The prefilter and the channel estimation filter are each adapted to the variable radio channel with the aid of the estimated symbols obtained from the viterbi analyzer. This analyzer uses the filter coefficients in the channel estimation filter to perform symbol estimation, in a known manner. The metric calculation in the viterbi analyzer is non-quadratic and is simplified in comparison with the quadratic metric calculation normally used. This non-quadratic metric calculation can be used because the received signal has been filtered in the prefilter. The simplified method defined in the Ungerboeck article requires certain restrictions in the adaptation algorithm, as illustrated in an article in Proceedings of the IEEE, Vol. 73, No. 9, September 1985, pages 1370-1372 by S.U.H. Qureshi: "Adaptive Equalization". The restrictions are required because the channel estimation filter and the prefilter are each separately adapted with the aid of the estimated symbols. This can result in all of the coefficients in the two filters converging towards zero. The restrictions are introduced with the intention of counteracting this convergence, these restrictions, for instance, comprising assigning a fixed value to one of the coefficients in the channel estimation filter. On the other hand, these restrictions render the simplified method less suited for use with fast varying channels, for instance fast fading channels. The problem that occurs resides in the lack of time in which to achieve this adaptation and, in principle, the same sort of problem of following the channel behaviour occurs as that occurring in a linear or a DFE-equalizer (Decision Feed Back). Expressed in simple terms, this means that an attempt is made to follow the inverted impulse response of the channel rather than the actual channel impulse response itself, and it is well known that the channel has, in general, a much slower changing rate than its inverse.
The second of the aforesaid problems, the fading problem, has earlier been solved, as described for instance in Swedish Patent Application SE 9102612-0, which corresponds to U.S. patent application Ser. No. 07/942,270 filed Sep. 9, 1992. A complex value signal is transmitted between transmitter and receiver and the signal strength of the signal varies very quickly and has abrupt fading dips. According to this patent application, it is observed that the real and imaginary components of the signal each vary relatively regularly and that the time derivatives of these components are often almost linear. This is utilized to estimate both the radio channel impulse response and the derivative of the impulse response. This derivative estimate is used to estimate the impulse response after a fading dip, during which the radio signal has been practically extinguished. A similar method is described in a dissertation by Lars Lindblom: "Adaptive Equalization for Fading Mobile Radio Channels", System and Control Group, Department of Technology, Uppsala University, 1992.